docs: introduce docs site (#141)

Signed-off-by: Panos Vagenas <35837085+vagenas@users.noreply.github.com>

docs/examples/batch_convert.py

@@ -0,0 +1,105 @@
+import json
+import logging
+import time
+from pathlib import Path
+from typing import Iterable
+
+from docling.datamodel.base_models import ConversionStatus
+from docling.datamodel.document import ConversionResult, DocumentConversionInput
+from docling.document_converter import DocumentConverter
+
+_log = logging.getLogger(__name__)
+
+
+def export_documents(
+    conv_results: Iterable[ConversionResult],
+    output_dir: Path,
+):
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    success_count = 0
+    failure_count = 0
+    partial_success_count = 0
+
+    for conv_res in conv_results:
+        if conv_res.status == ConversionStatus.SUCCESS:
+            success_count += 1
+            doc_filename = conv_res.input.file.stem
+
+            # Export Deep Search document JSON format:
+            with (output_dir / f"{doc_filename}.json").open(
+                "w", encoding="utf-8"
+            ) as fp:
+                fp.write(json.dumps(conv_res.render_as_dict()))
+
+            # Export Text format:
+            with (output_dir / f"{doc_filename}.txt").open("w", encoding="utf-8") as fp:
+                fp.write(conv_res.render_as_text())
+
+            # Export Markdown format:
+            with (output_dir / f"{doc_filename}.md").open("w", encoding="utf-8") as fp:
+                fp.write(conv_res.render_as_markdown())
+
+            # Export Document Tags format:
+            with (output_dir / f"{doc_filename}.doctags").open(
+                "w", encoding="utf-8"
+            ) as fp:
+                fp.write(conv_res.render_as_doctags())
+
+        elif conv_res.status == ConversionStatus.PARTIAL_SUCCESS:
+            _log.info(
+                f"Document {conv_res.input.file} was partially converted with the following errors:"
+            )
+            for item in conv_res.errors:
+                _log.info(f"\t{item.error_message}")
+            partial_success_count += 1
+        else:
+            _log.info(f"Document {conv_res.input.file} failed to convert.")
+            failure_count += 1
+
+    _log.info(
+        f"Processed {success_count + partial_success_count + failure_count} docs, "
+        f"of which {failure_count} failed "
+        f"and {partial_success_count} were partially converted."
+    )
+    return success_count, partial_success_count, failure_count
+
+
+def main():
+    logging.basicConfig(level=logging.INFO)
+
+    input_doc_paths = [
+        Path("./tests/data/2206.01062.pdf"),
+        Path("./tests/data/2203.01017v2.pdf"),
+        Path("./tests/data/2305.03393v1.pdf"),
+        Path("./tests/data/redp5110.pdf"),
+        Path("./tests/data/redp5695.pdf"),
+    ]
+
+    # buf = BytesIO(Path("./test/data/2206.01062.pdf").open("rb").read())
+    # docs = [DocumentStream(filename="my_doc.pdf", stream=buf)]
+    # input = DocumentConversionInput.from_streams(docs)
+
+    doc_converter = DocumentConverter()
+
+    input = DocumentConversionInput.from_paths(input_doc_paths)
+
+    start_time = time.time()
+
+    conv_results = doc_converter.convert(input)
+    success_count, partial_success_count, failure_count = export_documents(
+        conv_results, output_dir=Path("./scratch")
+    )
+
+    end_time = time.time() - start_time
+
+    _log.info(f"All documents were converted in {end_time:.2f} seconds.")
+
+    if failure_count > 0:
+        raise RuntimeError(
+            f"The example failed converting {failure_count} on {len(input_doc_paths)}."
+        )
+
+
+if __name__ == "__main__":
+    main()